In your research and teaching, you argue that climate change is a problem of social sciences. Why is that so?
I usually approach this question by first thinking about what kind of a problem climate change is not. And the way I think about it is that it’s not a natural science problem because climate science is mostly settled: we know that we are causing dangerous emissions, those are causing climate change and something needs to be done about it. Of course, we still need more information from the natural sciences and the climate change predictions and models get better all the time. But there’s nothing drastically changing, we know more or less what’s the case.
Other people say that it’s an economic problem. But I don’t think it’s so much of that really. Mitigating climate change costs money, but not doing it costs much more. There are different estimates, but they basically say that it may cost two to five percent of global GDP annually to make the changes we need to make. But if we don’t make them, it will cost five to ten percent, because the catastrophic scenarios start to happen and we will need to adapt to much more serious climate change. The exact numbers are quite difficult to evaluate, but the consensus among economists pretty much is that it’s cheaper to mitigate than not to mitigate climate change. So in that sense, it’s not an economic problem, we have the resources to do it. It’s more of a problem of who pays.
And the third thing that it’s not is a technological problem. Some people say “oh we need more technological development and that will solve climate change”. But I think that we already have all the necessary technologies. We have energy technologies that are new and fancy, we have new electricity production solutions, smart grids, electric cars and whatnot. We also have many old technology solutions that we are not using to the full effect: there could be lot more bicycles, more windmills, there’s a lot of work still to be done in insulating houses and making heating more efficient. Some of this technology is old, but it’s actually a very good use of money.
So I think climate change is not so much a problem of the natural sciences, economics or technological sciences. To solve the problem of climate change, what we need most is social sciences. We have enough natural science knowledge about climate change to act on it, but there is work to be done in communicating climate science to the public and the decision-makers, and that’s a social science problem. The economic problem is not so much about whether we have the money but how should the costs be distributed between countries and businesses and individuals, and that’s a social science question. And also the technology side of things, in a way, is a social science question. We need to ask what policy makers can do to make new technologies develop quicker and be adopted quicker. Because the development of most of the technologies that are changing the world right now was originally subsidized by states. The internet was first developed by the US military and by universities. The same goes for GPS, touch screens, voice recognition, you name it. Private companies only took them up once they could be commercialized. So we need social sciences to develop better technology and innovation policies, and we also need social scientific knowledge about how people adopt these new technologies. So there is certainly lots of work for social scientists in helping to deal with climate change.
The COMPON research group, which you are part of, studies the differences in countries' policies on climate change through the analysis of media discourses and networks of organizations that have the most significant impact on climate development. As your research suggests, these differences are quite wide. What do you think are the main factors that shape a country’s approach towards climate change policy?
There are a lot of things of course, and one of the very obvious ones is the economic structure. There are countries that are very dependent on fossil fuels or energy-intensive industries, and they tend to do worse on climate change mitigation. But what we are particularly interested in is not just saying “look, it’s all about the economy”, because that’s only a part of the explanation. When you dig deeper, you must ask: Okay, so maybe these fossil fuel industries have a lot of economic weight, how does their economic importance translate into political power? How do they operate to influence policies? Who do they collaborate with and who are they up against? And that’s where we get to policy network analysis, which is what we do.
So to keep to this example of fossil fuel industries, we try to see what kind of organizations they operate through, what other organizations they connect with, such as what political parties support them. But also what other organizations do. For example, we see some interesting dynamics in how business interest organizations sometimes work together with labour unions, who may be on the opposite side in some questions, but sometimes in the climate question they are on the same side because they are afraid of economic losses and losing jobs. So there might be this kind of a coalition, which is something we’ve observed in our earlier studies on Finland. On the other hand, there are coalitions consisting of environmental organizations, green political parties, and increasingly green businesses that are now pushing for stronger climate change measures. So these are the dynamics we are interested in: how organizations work together, to either push for, or to oppose stronger climate change mitigation policies. And I think that understanding that is the key to understanding the differences in climate change policies between countries.
The COMPON project is modular, which means that it can be used by another researcher or team who can do the analysis in their own country and then compare it with what’s already been done. Is this something that new researchers are interested in?
Yes. This was originally started by Jeff Broadbent at the University of Minnesota and some of his colleagues in different countries. They started with country case studies and some comparative media analyses. But since I became the chair of the international COMPON research network we’ve grown to I think fourteen countries. We systematized some of the methods and developed some new approaches here in Helsinki, and these were adopted by new country teams for example in India, Australia, the Czech Republic… Now we have a second round of surveys going on in many countries, for example Canada, Japan, Germany, Switzerland, the US, Ireland, Australia, India… So yeah, there’s been a lot of interest, and a lot of research teams reached out and started working with us.
The word used to spread quite efficiently in academic conferences, where we would present papers, and then we would say in the end that you guys are welcome to do this in your country, and we got a lot of new countries onboard. Right now, when the conferences have been on hold or online, that hasn’t happened so much. And also, the more countries you have the more difficult it is to manage. So we haven’t been promoting it so actively recently, and we are focusing our energies more on countries that we already have, and on following them over time. So it’s been a few years since we’ve had new countries come in. But we have expressions of interest, someone now wants to do it in Tanzania, so we will see if we can manage that…
Another project of yours is the course Global Climate Governance, which has been organized in cooperation with data science students from Aalto University last year. The students in the course were working in groups on a project related to climate governance. This idea of pairing social science students and students of technical fields sounds really interesting, but how was it working in practice? Do you think that students are prepared to work in this kind of multidisciplinary environment?
It worked better than I had expected. We knew it was going to be experimental, but it worked very well. And they did get very interesting projects underway. Some are now being developed into research papers, others are being developed into MA theses, so there has been actually pretty nice work coming out of that course. And we also explicitly had lectures and sessions where we talked about this kind of interdisciplinary work, so I think it was really useful for everyone. Of course, it is a lot of work to gather this kind of data and do all the analyses within one course. So ideally we would have an even bigger course, like 10 credits, and everyone could spend a bit more time doing this. But I think that even the kind of course that we had was really good.
This year it will be a little bit different. Not because it didn’t work last year, but the people we worked with at Aalto had another course going on that was social science related, and there are not so many people who do data science at Aalto that are interested in social sciences to have two courses like this in one spring. So that’s why we decided for this spring, it will be only the Helsinki students, they will still do research projects, but they will just use the methods they can master themselves. But hopefully, the year after we will do it again with Aalto.
It was also useful for us teachers. The way we run it was kind of a flipped classroom setting where people would read papers and listen to talks from videos, and then they would come to class on zoom and we would have breakout rooms where everyone would actually work on their projects in class time. And we as teachers could go around different rooms and try to help people with their projects. So in this sense, I think we also learned quite a bit. And I was surprised how well the Aalto students were equipped to interact with social scientists and to take on the questions that the social science students said would be interesting.
You already touched upon it a little bit, so are there any interesting projects coming up from the course?
Yes, there are several… For example, a couple of people are now working on the role of civil society organizations in Finnish climate change politics. They are using network data from the COMPON project, the policy network data that we just discussed and some Twitter data we’ve also collected. Basically they’re looking at what makes CSOs influential in climate politics. That’s one project that I know that is progressing on at least a couple of different fronts.
There was also a very interesting one where one of teams looked at science communication on Twitter, sharing scientific articles about climate change and how those sharing patterns work and who shares what, and whether those patterns changed with the Covid-19 pandemic. So that’s another course project that’s being developed into a research article right now.